Oracle Shifts Grid Focus to the Application

By Dennis Barker

October 1, 2008

Oracle’s newest candidate to solve some of IT Nation’s biggest problems has now officially hit the campaign trail, and its name is WebLogic Application Grid. This new assemblage of software is meant to put grid capabilities at the foundation of an organization’s computing operations by pooling IT resources and allocating them to workloads as needed.

“Think of WebLogic Application Grid as similar to a service-oriented architecture,” said Mike Piech, an Oracle senior director of product marketing, during a recent briefing. “It’s not a single product, not a single technology, but an infrastructure with a certain set of characteristics to provide on-demand behavior. Our approach is to have all the foundation-level middleware technologies play into that basic idea of the grid: pooling and sharing resources, using them more efficiently, but also providing a higher quality of service.”

As Piech alluded, WebLogic Application Grid has many different components. WebLogic, the application server Oracle acquired when it bought BEA Systems last year, can be thought of as the core constituent. But to turn it into an application grid server, the company added several of its Fusion Middleware technologies (Application Grid is considered part of the Fusion collection), starting with a new version of Coherence, its in-memory data grid. Coherence provides scale-out capability by dynamically partitioning data in memory across multiple servers, and, Oracle says, ensuring that data is continuously available. The new version 3.4 supports C/C++ so that the many programs written in those languages can take advantage of grid capabilities.

One of the key foundation blocks of the Application Grid is the Java virtual machine, and Oracle’s JRockit Real-Time can deliver “extreme transaction processing performance” to Java applications, Piech said.

“Deterministic garbage collection is a key differentiator that Oracle is providing here,” said Steve Harris, senior vice president of product development for server technologies, during a webcast. “It gives you this predictable, low-latency, high-throughput performance on Java that separates it from other offerings.”

JRockit Mission Control gives the developer and the datacenter better insight into how Java apps are performing, so they’re easier to fix when there are application-level issues, Oracle says. “You get detailed information about how code is executing, where latency is, and so on, and it’s all presented in an easily consumable interface environment,” Harris said. “That information is gathered by the JVM at all times and exposed to the user.”

Further into the stack, there’s Tuxedo (from BEA), the veteran distributed transaction processing platform, which Harris described as “pretty much the original scale-out-on-standard-hardware solution … [that] brings grid-like capability to the C/C++ world, as well as leveraging the memory grid capabilities of Coherence.”

Grid Belongs in the Middle

For Oracle, it’s all about the middleware. That’s where grid capabilities belong, the company says. “You need intelligence in the middle layer between hardware resources and the applications taking advantage of them,” said Hasan Rizvi, senior vice president for Fusion Middleware products, during a webcast detailing Oracle’s application grid strategy for customers and analysts.
“The Application Grid is the notion of taking a shared pool of resources and applying it to the workloads you have. At Oracle, we have been working on this for many years. We addressed this first at the database level. But how do we take that now to the next level, for the application environment?” By sharing and pooling resources at a higher level of the stack — applying it to middleware that sits right beneath your apps.

Rizvi said the first business benefit of this approach is cost efficiency. “If you’re able to manage your resources in a way that is shared and available to all workloads, it gives you lower operational costs. A common environment lets you reduce not just hardware costs but the human element of what you need to run that environment,” he said.

Another major advantage is “risk-free scale-out,” Piech said in an earlier briefing. “As demand goes up, you need to be able to dynamically add capacity to those SOA services. In the past, that involved taking the service down, rehosting it on a bigger machine, or taking it down to add new nodes…What we are providing is the ability to create a grid with Fusion Middleware. You can scale out dynamically with low or no risk.

“Here’s an example. A large auto insurance company in periods of high growth and demand can add memory capacity without taking the app down. Coherence lets IT add nodes so that it’s transparent to end users.”

When a customer asked during the web briefing, “Does this mean I now have to scrap my Oracle App Server 10.3 and rebuild using the BEA architecture stack?” Rizvi said no. “This is an ongoing investment we have to take advantage of grid capabilities. It’s not a change in direction or taking a right turn or whatever. We’re advancing the infrastructure to better provide the services customers need.”

Asked if Application Grid is “cloud computing in the enterprise,” Oracle officials said, well, not really, although some of the concepts are the same.

Noting that cloud computing means different things to people, Rizvi said, “We are not proposing outsourcing your IT department, which is one definition. But it is related to cloud computing and to virtualization in the sense of being able to provision machines quickly and easily, giving IT operations scalability.”

Harris elaborated. “If you take Coherence as a case in point,” he said, “we have customers who are distributing their data across a data grid of hundreds of nodes, which is very cloudlike in some cloud sense of the word. Now, those customers can then take advantage of the compute power across that [grid]. If you are a WebLogic customer who’s written a standard J2EE app that is sharing session state using J2EE mechanisms, that session state can be shared across the grid also. No one has to change any app to take advantage of that.”

Oracle declined to mention specific customers using the new grid platform, but Adam Messinger, vice president of development for Fusion Middleware, says its capabilities are particularly appealing to financial services, for example, because of quick recovery time if a machine fails and failover with a minimum of service disruption. Scalability and performance attributes bestowed by Coherence enable financial analysts to compute risk values “in minutes instead of hours and days,” he said. “They can trade in ways they couldn’t before.”

Doing things faster remains the objective. “IT is more and more an enabler of business strategy, so you need to reduce the time it takes to absorb business-driven priorities without having to take months and weeks to figure that out,” Rizvi said. “With the grid you can actually shrink the time it takes for you to get the requirements from business and react to that because you have a much more flexible environment, and that flexibility is an important element. With the grid approach you have baked-in high availability, baked-in high reliability. There’s a lot of redundancy built into the system so you don’t have to worry about it for every application.

“This normally requires rocket science to get it right, but [our approach] brings that into the platform. You can react to these workloads and increase the resources available to them. The way to do that is to provide that intelligence in the software. We can essentially do this out of the box so you don’t have to worry about it for each application.”

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

China’s Expanding Effort to Win in Microchips

July 27, 2017

The global battle for preeminence, or at least national independence, in semiconductor technology and manufacturing continues to heat up with Europe, China, Japan, and the U.S. all vying for sway. A fascinating article ( Read more…

By John Russell

Hyperion: Storage to Lead HPC Growth in 2016-2021

July 27, 2017

Global HPC external storage revenues will grow 7.8% over the 2016-2021 timeframe according to an updated forecast released by Hyperion Research this week. HPC server sales, by comparison, will grow a modest 5.8% to $14.8 Read more…

By John Russell

Exascale FY18 Budget – The Senate Provides Their Input

July 27, 2017

In the federal budgeting world, “regular order” is a meaningful term that is fondly remembered by members of both the Congress and the Executive Branch. Regular order is the established process whereby an Administrat Read more…

By Alex R. Larzelere

HPE Extreme Performance Solutions

HPE Servers Deliver High Performance Remote Visualization

Whether generating seismic simulations, locating new productive oil reservoirs, or constructing complex models of the earth’s subsurface, energy, oil, and gas (EO&G) is a highly data-driven industry. Read more…

India Plots Three-Phase Indigenous Supercomputing Strategy

July 26, 2017

Additional details on India's plans to stand up an indigenous supercomputer came to light earlier this week. As reported in the Indian press, the Rs 4,500-crore (~$675 million) supercomputing project, approved by the Ind Read more…

By Tiffany Trader

Exascale FY18 Budget – The Senate Provides Their Input

July 27, 2017

In the federal budgeting world, “regular order” is a meaningful term that is fondly remembered by members of both the Congress and the Executive Branch. Reg Read more…

By Alex R. Larzelere

India Plots Three-Phase Indigenous Supercomputing Strategy

July 26, 2017

Additional details on India's plans to stand up an indigenous supercomputer came to light earlier this week. As reported in the Indian press, the Rs 4,500-crore Read more…

By Tiffany Trader

Tuning InfiniBand Interconnects Using Congestion Control

July 26, 2017

InfiniBand is among the most common and well-known cluster interconnect technologies. However, the complexities of an InfiniBand (IB) network can frustrate the Read more…

By Adam Dorsey

NSF Project Sets Up First Machine Learning Cyberinfrastructure – CHASE-CI

July 25, 2017

Earlier this month, the National Science Foundation issued a $1 million grant to Larry Smarr, director of Calit2, and a group of his colleagues to create a comm Read more…

By John Russell

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

Fujitsu Continues HPC, AI Push

July 19, 2017

Summer is well under way, but the so-called summertime slowdown, linked with hot temperatures and longer vacations, does not seem to have impacted Fujitsu's out Read more…

By Tiffany Trader

Researchers Use DNA to Store and Retrieve Digital Movie

July 18, 2017

From abacus to pencil and paper to semiconductor chips, the technology of computing has always been an ever-changing target. The human brain is probably the com Read more…

By John Russell

The Exascale FY18 Budget – The Next Step

July 17, 2017

On July 12, 2017, the U.S. federal budget for its Exascale Computing Initiative (ECI) took its next step forward. On that day, the full Appropriations Committee Read more…

By Alex R. Larzelere

Google Pulls Back the Covers on Its First Machine Learning Chip

April 6, 2017

This week Google released a report detailing the design and performance characteristics of the Tensor Processing Unit (TPU), its custom ASIC for the inference Read more…

By Tiffany Trader

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Just how close real-wo Read more…

By John Russell

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its a Read more…

By Tiffany Trader

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the cam Read more…

By John Russell

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

May 10, 2017

At Nvidia's GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company's much-anticipated Volta architecture a Read more…

By Tiffany Trader

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Leading Solution Providers

Facebook Open Sources Caffe2; Nvidia, Intel Rush to Optimize

April 18, 2017

From its F8 developer conference in San Jose, Calif., today, Facebook announced Caffe2, a new open-source, cross-platform framework for deep learning. Caffe2 is the successor to Caffe, the deep learning framework developed by Berkeley AI Research and community contributors. Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurrencies like Bitcoin, along with classified government communications and other sensitive digital transfers. Read more…

By Doug Black

MIT Mathematician Spins Up 220,000-Core Google Compute Cluster

April 21, 2017

On Thursday, Google announced that MIT math professor and computational number theorist Andrew V. Sutherland had set a record for the largest Google Compute Engine (GCE) job. Sutherland ran the massive mathematics workload on 220,000 GCE cores using preemptible virtual machine instances. Read more…

By Tiffany Trader

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the Read more…

By John Russell

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of Read more…

By Alex Woodie

Six Exascale PathForward Vendors Selected; DoE Providing $258M

June 15, 2017

The much-anticipated PathForward awards for hardware R&D in support of the Exascale Computing Project were announced today with six vendors selected – AMD Read more…

By John Russell

Top500 Results: Latest List Trends and What’s in Store

June 19, 2017

Greetings from Frankfurt and the 2017 International Supercomputing Conference where the latest Top500 list has just been revealed. Although there were no major Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Share This